Monitoring objects capable of wireless communications

ABSTRACT

A method of monitoring objects capable of wireless communications is provided. The method comprises detecting an activity performed by a user of a wireless communications device, acquiring information identifying an expected set of objects which are associated with the detected activity, determining whether at least one of the objects in the expected set is not in proximity of the wireless communications device, and if so notifying the user that at least one of the objects in the expected set is not in proximity of the wireless communications device.

TECHNICAL FIELD

The invention relates to a method of monitoring objects capable ofwireless communications, a device for monitoring objects capable ofwireless communications, a corresponding computer program, and acorresponding computer program product.

BACKGROUND

In the art, there are methods available to detect proximity of devicesbased on technologies like Near-Field Communication (NFC), e.g.,Radio-Frequency Identification (RFID), Bluetooth, 6LOWPAN (“IPv6 overLow Power Wireless Personal Area Networks”), and the like.

These technologies may be used for resolving issues relating toanti-theft, child security, providing reminders, and the like.Typically, the user has to configure a tracker application/device andthe device(s) to be tracked, after which the tracker issues alarms ifthe tracked device(s) is/are not in proximity of the tracker, i.e.,is/are outside a predetermined range from the tracker. For instance, achild may be provided with a tracked device in the form of a small radiotransmitter, and the tracker device will sound an alarm if the childmoves outside of a pre-defined area.

However, these prior art methods are inadequate when the set of devicesin the proximity of the individual changes dynamically depending uponthe environment and activities performed by the individual. The problemis being further aggravated due to the rapid increase ofInternet-of-Things (IoT) devices like sensors, wearables, mobile phones,etc.

SUMMARY

An object of the present invention is to solve, or at least mitigate,this problem in the art and to provide an improved method of monitoringobjects capable of wireless communications. This object is attained in afirst aspect of the invention by a method of monitoring objects capableof wireless communications. The method comprises detecting an activityperformed by a user of a wireless communications device, acquiringinformation identifying an expected set of objects which are associatedwith the detected activity, determining whether at least one of theobjects in the expected set is not in proximity of the wirelesscommunications device, and if so notifying the user that at least one ofthe objects in the expected set is not in proximity of the wirelesscommunications device.

This object is attained in a second aspect of the invention by a devicefor monitoring objects capable of wireless communications, the devicecomprising a processing unit and a memory. The memory containsinstructions executable by the processing unit, whereby the device isoperative to detect an activity performed by a user of a wirelesscommunications device, acquire information identifying an expected setof objects which are associated with the detected activity, determinewhether at least one of the objects in the expected set is not inproximity of the wireless communications device, and if so to notify theuser that at least one of the objects in the expected set is not inproximity of the wireless communications device.

Hence, a device referred to as a tracker device, being for instance amobile phone, a mobile terminal, a User Equipment (UE), or a smartphoneof a user, detects that a certain activity is performed by the user. Forinstance, it may be detected that the user performs an activity such as“Go To Work” upon leaving her home premises during a time windowspecified for the activity (“Any Weekday, 07:00-08:00”).

To this end, a change in location of the user may, e.g., be detectedusing a Global Positioning System (GPS) of the tracker device (from afirst location “on home premises” to a second location “off homepremises”, or “leaving home premises”).

Thereafter, information is acquired identifying an expected set ofobjects which are associated with the detected activity, such as awallet, a home key and a work pass.

It is noted that the objects are required to be equipped with wirelesscommunications capability such as Near Field Communication (NFC)technology in the form of, e.g., a Radio-Frequency Identification (RFID)tag, a Bluetooth transmitter, or any other short-range radiotransmitter, for communicating with the tracker device.

If it is determined that any one or more of the objects included in theexpected set, e.g., the wallet, is not in proximity to the trackerdevice when the tracker device leaves the home premises of the userduring the time window specified for the activity, as detected by meansof, e.g., NFC-based communications between the tracker device and theobjects, the user is notified accordingly.

Hence, if it is concluded that one or more of the objects in theexpected set is not in proximity of the tracker device upon the userperforming the activity (i.e., one or more of the objects are outside aproximity range of the tracker device), in this case leaving the homepremises on a weekday between 7 and 8 AM, the user is advantageouslynotified accordingly. The user is thus made aware that she forgot one ormore of the objects of the expected set associated with this particularactivity and can go back into her house to pick up any forgotten objectof the expected set before leaving for work.

In an embodiment, the user is notified by the tracker device emitting anaudible sound, displaying a message, generating a haptic notificationsuch as a vibration, etc. In an alternative embodiment, the trackerdevice may signal another wireless communications device that the usershould be notified, for instance by requesting the user's smartwatch tovibrate, or requesting the user's car to not start the engine and/ordisplay a message on the dashboard.

The method of monitoring the objects may be performed by the trackerdevice, a node of a communications network which is accessible by thewireless communications device, e.g., an application server, or one ormore nodes of a cloud environment which is accessible by the wirelesscommunications device. It is envisaged that a distributed solution maybe provided, wherein the tracker device performs one or more steps ofthe method, while one or more cloud devices performs any further steps.

In a further embodiment, an actual set of objects which are in proximityof the wireless communications device is determined, and it is furtherdetermined whether at least one of the objects in the expected set isnot in the actual set. If so, the user is notified accordingly.

In still a further embodiment, after or prior to notifying the user thatone or more of the objects included in the expected set has not beendetected as being in proximity to the tracker device, the user isqueried as to whether any objects of the determined actual set are to beadded to the expected set associated with the detected activity. If so,an updated expected set may be stored in a database comprisingactivities and corresponding expected sets of objects.

In yet another embodiment, after the user has been notified that one ormore of the objects included in the expected set have not been detectedas being in proximity to the tracker device, the user is queried as towhether one or more objects of the expected set associated with thedetected activity are to be removed from the expected set to create anupdated expected set for the detected activity. If so, an updatedexpected set may be stored in a database comprising activities andcorresponding expected sets of objects.

In another embodiment, the activity which is performed by the user ofthe wireless communications device is detected based on at least one of,a combination, or a pattern, of: a location of the wirelesscommunications device or a change thereof, a motion pattern of thewireless communications device or a change thereof, a date, a time ofday, a calendar event, a communication event, sensor readings, andcurrent weather conditions.

In still a further embodiment, a behaviour of the user is registered,and if it is concluded that the registered behaviour is a frequentlyoccurring behaviour of the user, the registered behaviour is specifiedas an activity.

In still another embodiment, a group of objects are registered as beingcarried by the user when the frequently occurring behaviour of the useris registered, the group of objects being specified as the expected setof objects associated with the specified activity.

Further provided is a computer program comprising computer-executableinstructions for causing the device to perform steps according to anembodiment of the first aspect of the invention, when thecomputer-executable instructions are executed on a processing unitincluded in the device.

Further provided is a computer program product comprising a computerreadable medium, the computer readable medium having an embodiment ofthe computer program embodied thereon.

Generally, all terms used in the claims are to be interpreted accordingto their ordinary meaning in the technical field, unless explicitlydefined otherwise herein. All references to “a/an/the element,apparatus, component, means, step, etc.” are to be interpreted openly asreferring to at least one instance of the element, apparatus, component,means, step, etc., unless explicitly stated otherwise. The steps of anymethod disclosed herein do not have to be performed in the exact orderdisclosed, unless explicitly stated.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention is now described, by way of example, with reference to theaccompanying drawings, in which:

FIG. 1 illustrates a scenario where a user of a wireless communicationsdevice is monitored leaving the home premises for work, in accordancewith embodiments of the invention.

FIG. 2 shows a flowchart illustrating an embodiment of a method ofmonitoring objects capable of wireless communications.

FIG. 3 shows a sequence diagram illustrating the embodiment of themethod of monitoring objects capable of wireless communicationsaccording to FIG. 2, performed by the wireless communications device ofthe user.

FIG. 4 shows a sequence diagram illustrating an embodiment of the methodof monitoring objects capable of wireless communications, performed by aremotely located network node.

FIG. 5 shows a sequence diagram illustrating another embodiment of themethod of monitoring objects capable of wireless communications.

FIG. 6 shows a sequence diagram illustrating yet another embodiment ofthe method of monitoring objects capable of wireless communications.

FIG. 7 shows a sequence diagram illustrating still another embodiment ofthe method of monitoring objects capable of wireless communications.

FIG. 8 shows a sequence diagram illustrating still a further embodimentof the method of monitoring objects capable of wireless communications.

FIG. 9 shows a sequence diagram illustrating yet a further embodiment ofthe method of monitoring objects capable of wireless communications.

FIG. 10 shows a device for monitoring objects capable of wirelesscommunications, in accordance with an embodiment of the invention.

FIG. 11 shows a device configured to monitor objects capable of wirelesscommunications, in accordance with another embodiment of the invention.

DETAILED DESCRIPTION

The invention will now be described more fully hereinafter withreference to the accompanying drawings, in which certain embodiments ofthe invention are shown. This invention may, however, be embodied inmany different forms and should not be construed as limited to theembodiments set forth herein; rather, these embodiments are provided byway of example so that this disclosure will be thorough and complete,and will fully convey the scope of the invention to those skilled in theart. Like numbers refer to like elements throughout the description.

FIG. 1 illustrates an exemplifying embodiment of the invention.Commonly, when an individual or user 10 leaves home 11 for work everymorning, she will want to bring with her a set of objects that she willneed during her work day, which set in this particular example isexemplified as comprising her wallet 12, home key 13, and work pass 14to be used for entering work premises.

This set 15 of objects is referred to as the expected set of objects.That is, when the individual 10 with which the objects 12, 13, 14 areassociated leaves home for work, she 10 is expected to carry the objectsin the expected set 15 with her.

Individual 10 further carries a wireless communications device 16, inFIG. 1 exemplified as a smartphone 16. This wireless communicationsdevice 16 is referred to as a tracker device.

It is noted that the objects 12, 13, 14 are required to be equipped withwireless communications capability. Such capability is typically alreadypresent at the work pass 14 which oftentimes utilizes Near FieldCommunication (NFC) technology in the form of, e.g., Radio-FrequencyIdentification (RFID) for communicating with a corresponding reader atthe work premises.

Any objects not normally being equipped with wireless communicationsmeans, such as the wallet 12 and the key 13, may be provided withwireless communications means such as an RFID tag, a Bluetooth or6LoWPAN (“IPv6 over Low Power Wireless Personal Area Networks”)transmitter, or the like.

To this end, the objects 12, 13, 14 included in the expected set 15 arecapable of communicating wirelessly with the tracker device 16, in theform of a mobile phone, a smartphone, a mobile terminal, a UE, a tablet,a smartwatch, or any other appropriate wireless communications device,being equipped with a processing unit and a wireless communicationsinterface. As discussed, the tracker device 16 may communicate withobjects capable of wireless communications via any appropriate wirelesstechnology, such as RFID, Bluetooth, 6LoWPAN, any cellulartelecommunications technology (3G, 4G, 5G, etc), Wireless Local AreaNetwork (WLAN)/WiFi, etc. It may further be envisaged that the trackerdevice 16 communicates with one or more remotely located network nodes,such as for instance an application server 17 or one or more nodes of acloud environment which is/are accessible by the tracker device 16, forfetching stored data, for storing data, or for having the network nodeperform any computing functions on behalf of the tracker device 16.

Now, the expected set 15 of objects is associated with a particularactivity in which the user 10 of the tracker device 16 is to partake, inthis exemplifying embodiment an activity defined as “going to work”.Hence, the following associations are made at the tracker device 16and/or the server 17:

Expected_Set_of_Devices=“Wallet, Key, Work Pass”;

Expected_Set_of_ Devices→Activity=“Go to Work”

The activity can be specified in many different ways, e.g., as a timewindow set to “Any Weekday, 07:00-08:00”. In this exemplifyingembodiment, the activity may further specify a location criterion whichis associated with the tracker device 16 used by the user 10.

Similar to the above specified activity, the location criterioncomprised in the activity can be specified in numerous ways depending onthe particular implementation, in this exemplifying embodiment forinstance as “Leave Home”. The tracker device 16 will accordingly detectindirectly whether at least one of the objects 12, 13, 14 in theexpected set 15 complies with this predetermined location criterion bydetermining whether it complies with this predetermined locationcriterion itself.

Hence, the expected set 15 of objects may be associated with thespecified activity as:

Expected_Set_of_Devices→Activity=“Go to Work”=[Location=“Leave Home” ANDDay=“Any Weekday” AND Time=“07:00-08:00”]

It is envisaged that there are numerous options for specifying anactivity in which the user 10 is to partake. Further examples will begiven hereinbelow.

Reference is further be made to the flowchart of FIG. 2 for describingan embodiment of a method of monitoring objects capable of wirelesscommunications.

In a first step S101, it is detected that a specified activity isperformed by the user 10. In this embodiment, the user 10 is consideredto perform the activity upon leaving the home premises 11, which isdetected by means of the tracker device 16 leaving the home premises 11during the time window specified for the activity (“Any Weekday,07:00-08:00”). Hence, a change in location is detected, by detection achange in location of the tracker device 16 from a first location (“onhome premises”) to a second location (“off home premises”).

Thereafter, in step S102, information is acquired identifying anexpected set 15 of objects which are associated with the detectedactivity, in this case the wallet 12, the home key 13, and the work pass14. It can be envisaged that each object is given a unique numericalidentifier.

If it is determined in step S103 that any one or more of the objectsincluded in the expected set 15, e.g., the wallet 12, is not inproximity to the tracker device 16 when the tracker device leaves thehome premises 11 of the user 10 during the time window specified for theactivity, the user 10 is notified thereof in step S104. The respectivelocations of the objects 12, 13, 14 and the tracker device 16 may betracked using, e.g., Global Positioning System (GPS). Alternatively, itis envisaged that the location or position of tracker device 16 isdetermined using GPS, while the proximity of the objects 12, 13, 14 tothe tracker device is detected using, e.g., NFC or any other short-rangeradio technology between the tracker device 16 and the objects 12, 13,14.

Hence, if it is concluded that one or more of the objects 12, 13, 14 inthe expected set 15 are not in proximity of the tracker device 16 uponthe user 10 performing the activity (i.e., one or more of the objectsare outside a proximity range defined for the tracker device 16), inthis case leaving the home premises 11 on a weekday between 7 and 8 AM,the user 10 is advantageously notified accordingly. The user 10 is thusmade aware that she forgot one or more of the objects of the expectedset 15 associated with this particular activity and can go back into herhouse 11 to pick up any forgotten object of the expected set 15 beforeleaving for work.

Typically, in case all the objects 12, 13, 14 in the expected set 15 arein proximity of the tracker device 16, the user 10 is not notified, eventhough it could be envisaged that the user 10 is notified that allobjects of the expected set 15 have been successfully detected.

In an embodiment, the user 10 is notified by tracker device 16 emittingan audible sound, displaying a message, generating a haptic notificationsuch as a vibration, etc. In an alternative embodiment, the trackerdevice 16 may signal another wireless communications device that theuser 10 should be notified, for instance by requesting the user'ssmartwatch to vibrate, or requesting the user's car to not start theengine and/or display a message on the dashboard.

Now, in the above described embodiment, it may be envisaged that thetracker device 16 itself performs all steps S101-S104 for monitoring theobjects. Hence, the tracker device 16 detects in step S101 that it islocated outside of the home premises 11 (i.e., by detecting a change inits location from a first location to a second location as previouslydescribed) on a weekday at 07:00-08:00.

Thereafter, the tracker device 16 requests from a local data storage instep S102 information identifying the expected set 15 of objects whichare associated with the detected activity, and determines whether it iscapable of communicating, e.g., by NFC, with all the objects 12, 13, 14in the expected set 15 in step S103.

Alternatively, the tracker device 16 may measure the strength of asignal submitted by the respective object, and if the signal strength issufficient, i.e., exceeds a threshold value, the object is considered tobe in proximity of the tracker device 16.

If so, all the objects 12, 13, 14 of the expected set 15 are inproximity to the tracker device 16. If not, the tracker device 16notifies the user, and the user 10 is thus advantageously made awarethat she forgot one or more of the objects of the expected set 15associated with this particular activity and can go back into her house11 to pick up any forgotten object of the expected set 15 before leavingfor work.

FIG. 3 illustrates a sequence diagram where the method of monitoring isperformed in its entirety by the tracker device 16 according to anembodiment of the invention.

The tracker device 16 has access to one or more specified activities ofthe user 10, for instance fetched from a calendar app executing on theuser's smartphone (exemplified here as being the tracker device 16). Analternative approach is to have the tracker device 16 learn activitiesof the user, and even to associate a learned expected set of objectswith each learned activity.

For instance, after the tracker device 16 has (1) left the home premiseson (2) a weekday at (3) 07:00-08:00 at a number of occasions, it willdefine the activity “Go To Work” based on these three criteria. Further,by repeatedly detecting a set of objects in its proximity at theseoccasions, the tracker device 16 will form the expected set of objectsand associate the expected set with this activity.

Hence, a database may be maintained at the tracker device 16 specifyinga number of activities and an expected set of objects associated witheach of the activities:

TABLE 1a Database comprising activities and associated objects. ActivityExpected set of objects Activity1 Object1, Object2, Object3 Activity2Object1, Object4 Activity3 Object5

As can be seen in Table 1a, at least one object is associated with eachactivity, thereby creating the expected set of objects. One and the sameobject may be associated with different activities. In the exampleTable, Object1 is comprised in the expected set both for Activity1 andActivity2.

In this particular exemplifying embodiment, the tracker device 16detects in step S101 its location, e.g., using GPS, or by detecting thatit leaves a coverage area of the user's WLAN. If the location of thetracker device 16 changes from a first location (“on home premises”) toa second location (“off home premises”) on any weekday at 07:00-08:00,the user is considered to partake in this particular activity (“Go ToWork”). It is assumed that this corresponds to Activity1 in Table 1a.

Thereafter, in step S102, the tracker device 16 acquires informationidentifying an expected set of objects which are associated with thedetected activity from the stored database. To this end, the trackerdevice 16 maps the detected activity (“Activity1”) to the entries inTable 1a and concludes that the expected set 15 comprises Object1,Object2, and Object3, in this example corresponding to the wallet 12,the home key 13, and the work pass 14, respectively.

Further, the tracker device 16 determines in step S103 whether at leastone of the objects 12, 13, 14 in the expected set is not in itsproximity, upon the user performing the activity of going to work(“Activity1”). It is in this example assumed that the tracker device 16communicates with the objects utilizing NFC.

As is illustrated in FIG. 3, the tracker device 16 determines whetherthe objects 12, 13, 14 are in its proximity, for instance by making anattempt to communicate with the objects, or by measuring the strength ofa respective signal received from the objects. If the communicationattempt is successful, or if the signal strength exceeds a thresholdvalue, the object is considered to be in proximity of the tracker device16. Optionally, and indicator indicating “proximity” for each object canbe stored in the database, e.g., in the form of a signal strengththreshold defining “proximity” for that specific object.

In this particular example, the home key 13 and the work pass 14 are inproximity to the tracker device 16, while the wallet 12 is not.

The tracker device 16 determines in step S103 that the home key 13(“Object2”) and the work pass 14 (“Object3”) are in proximity to thetracker device 16, but that the wallet 12 (“Object1”) is not, therebyconcluding from Table 1a that not all the objects in the expected setfor Activity1 are in proximity to the tracker device 16.

As a consequence, the tracker device 16 notifies the user 10 in stepS104 by emitting an audio alert to the user 10, informing her about thelacking wallet 12. As an alternative, or in addition, to emitting anaudio alert, the tracker device 16 may optionally display a messagenotifying the user that an expected object is not in the user's 10proximity, preferably also identifying the missing object by name (e.g.,“You forgot your wallet.”).

FIG. 4 illustrates a sequence diagram where the method of monitoring isperformed partly or fully at one or more remotely located network nodes,thereby facilitating a cloud solution. In FIG. 4, the network node(s)is/are embodied by the server 17.

In this embodiment, the server 17 has access to one or more specifiedactivities of the user 10, for instance fetched from a calendar appexecuting on the user's smartphone (exemplified as being the trackerdevice 16) or from a cloud storage. In addition, sensor readings such asposition or location data may be transmitted from the tracker device 16to the server 17.

To this end, a database may be maintained at the server 17 specifying anumber of activities and an expected set of objects associated with eachof the activities, as previously described with reference to Table 1a.

In this particular exemplifying embodiment, the server 17 detects instep S101 the location of the tracker device 16 using GPS. If thetracker device 16 is leaving the user's 10 home premises 11 on anyweekday at 07:00-08:00, the activity (“Go To Work”) is detected. Again,it is assumed that this corresponds to Activity 1 in Table 1a.

Thereafter, in step S102, the server 17 acquires information identifyingan expected set of objects which are associated with the detectedactivity, from the stored database. To this end, the server 17 maps thedetected activity (“Activity1”) to the entries in Table 1a and concludesthat the expected set 15 comprises Object1, Object2 and Object3, in thisexample corresponding to the wallet 12, the home key 13, and the workpass 14, respectively.

Even though it may be envisaged that the server 17 communicates directlywith the objects capable of wireless communication, i.e., the wallet 12,the home key 13 and the work pass 14, for determining their proximity tothe tracker device 16 based on, e.g., GPS readings, it is in thisexample assumed that the tracker device 16 communicates with therespective object utilizing, e.g., NFC, and provides resultinginformation to the server 17. In case the server 17 would communicatedirectly with the objects 12, 13, 14, the method may be undertaken inits entirety “in the cloud”, either by the server 17 solely or incooperation with other remote nodes.

Hence, the server 17 acquires in step S103 a information as to whichobjects actually are in proximity to the tracker device 16 upon the userperforming the activity of going to work (“Activity1”).

As is illustrated in FIG. 4, the tracker device 16 concludes that thehome key 13 and the work pass 14 are in proximity to the tracker device16, but that the wallet 12 is not, which the tracker device 16 reportsaccordingly to the server 17.

The server 17 determines in step S103 that the home key 13 (“Object2”)and the work pass 14 (“Object3”) are in proximity to the tracker device16, but that the wallet 12 (“Object1”) is not, thereby concluding fromTable 1a that not all the objects in the expected set for Activity1 arein proximity to the tracker device 16.

As a consequence, the server 17 sends a notification to the user 10 viathe tracker device 16 in step S104, whereby the tracker device 16 emitsan audio alert to the user 10 advantageously informing her about herlacking wallet 12.

Again, as previously discussed, in case the server 17 would communicatedirectly with the objects 12, 13, 14, and notify the user 10 via, e.g.,her smartwatch (not shown), the tracker device 16 need not take anyactive part in the monitoring, not even causing an audio alert.

FIG. 5 illustrates a sequence diagram where the method of monitoring isperformed in its entirety by the tracker device 16 according to anotherembodiment. However, it is noted that this embodiment may also beimplemented by a remotely located network node, such as the server 17.

In this embodiment, all objects which are in proximity to the trackerdevice 16 are determined upon detecting that the user 10 partakes in aspecified activity. In the previously described embodiments of FIGS.2-4, only the objects comprised in the expected set are detected asbeing in proximity to the tracker device 16. Accordingly, as soon as allobjects 12, 13, 14 of the expected set have been detected, there is noneed to continue and detect any further proximate objects.

The objects determined to be in proximity to the tracker device 16 arereferred to as an actual set of objects.

As in the previous embodiment, the tracker device 16 detects in stepS101 its location, e.g., using GPS. If the tracker device 16 is leavingthe user's 10 home premises 11 on any weekday at 07:00-08:00, the useris considered to partake in the activity (“Go To Work”). It is assumedthat this corresponds to Activity1 in Table 1a.

Thereafter, in step S102, the tracker device 16 acquires informationidentifying an expected set of objects which are associated with thedetected activity from the stored database. To this end, the trackerdevice 16 maps the detected activity (“Activity1”) to the entries inTable 1a and concludes that the expected set 15 comprises Object1,Object2 and Object3, in this example corresponding to the wallet 12, thehome key 13, and the work pass 14, respectively.

Further, the tracker device 16 determines in step S103 b the actual setof objects being in proximity of the tracker device 16. As isillustrated in FIG. 5, the tracker device 16 determines that the homekey 13 and the work pass 14 are in proximity to the tracker device 16,but that the wallet 12 is not.

In this embodiment, the tracker device 16 further determines that asmartwatch 18 (“Object4”) is in proximity of the tracker device 16, forinstance by signalling based on Bluetooth or even via a Wireless LocalArea Network (WLAN), commonly referred to as “WiFi”.

The objects determined to be in the actual set in step S103 b are thusthe home key 13, the work pass 14, and the smartwatch 18, i.e., Object2,Object3, and Object4.

Next, in step S103, the tracker device 16 determines whether any objectin the expected set is not in the actual set. With reference to Table1a, the wallet 12 (“Object1”) is not in the actual set and thus not inproximity to the tracker device 16, upon the user performing theactivity of going to work (“Activity1”).

As a consequence, the tracker device 16 notifies the user 10 in stepS104 by emitting an audio alert and/or displaying a notification to theuser 10, advantageously informing her about the lacking wallet 12.

FIG. 6 illustrates a sequence diagram where the method of monitoring isperformed in its entirety by the tracker device 16 according to stillanother embodiment. However, it is noted that this embodiment may alsobe implemented at a remotely located network node, such as the server17.

As in the embodiment of FIG. 5, all objects being in proximity to thetracker device 16 upon detection of the user 10 performing a specifiedactivity are determined, thereby forming an actual set.

However, in addition to the steps of the embodiment described withreference to FIG. 5, after (or before) having notified the user 10 instep S104 that the wallet 12 included in the expected set has not beendetected as being in proximity to the tracker device 16, the user isqueried in step S105 as to whether any objects of the determined actualset are to be added to the expected set which is associated with thedetected activity.

The user responds in step S106, in this particular example with theresponse that the smartwatch 18 is to be added to the expected set forActivity1.

The tracker device 16 will thus update its database of Table 1a in stepS107, resulting in updated Table 1b:

TABLE 1b Updated database comprising activities and associated objects.Activity Expected set of objects Activity1 Object1, Object2, Object3,Object 4 Activity2 Object1, Object4 Activity3 Object5

FIG. 7 illustrates a sequence diagram where the method of monitoring isperformed in its entirety by the tracker device 16 according to still afurther embodiment. However, it is noted that this embodiment may alsobe implemented at a remotely located network node, such as the server17.

As in the embodiment of FIG. 5, all objects being in proximity to thetracker device 16 upon detection of the user 10 performing a specifiedactivity are determined, thereby forming an actual set. It is noted thatin this embodiment, it is not necessary to determine an actual set.Rather, steps S108 and S109 as will be described in the following mayfollow on step s104 in either of the embodiments in FIGS. 3 and 4.

Now, in addition to the steps of the embodiment of FIG. 5, after havingnotified the user 10 in step S104 that the wallet 12 included in theexpected set has not been detected as being in proximity to the trackerdevice 16, the user 10 is given the opportunity in step S108 to indicateas to whether one or more objects of the expected set associated withthe detected activity are to be removed from the expected set to createan updated expected set for the detected activity.

In this example, the user 10 indicates that the wallet 12 (“Object1”) isto be removed from the expected set illustrated in Table 1a, wherein thetracker device 16 updates its database of Table 1a in step S109,resulting in updated Table 1c:

TABLE 1c Updated database comprising activities and associated objects.Activity Expected set of objects Activity1 Object2, Object3 Activity2Object1, Object4 Activity3 Object5

It is noted that the embodiments described in FIGS. 6 and 7 may becombined. That is, the user may add objects of the determined actualset, as well as remove objects from the expected set, wherein thetracker device 16 will update its database accordingly, as has beendescribed.

FIG. 8 illustrates a sequence diagram where the method of monitoring isperformed in its entirety by the tracker device 16 according to yetanother embodiment. However, it is noted that this embodiment may alsobe implemented at a remotely located network node, such as the server17.

As in the embodiments of FIGS. 5-7, all objects being in proximity tothe tracker device 16 upon detection of the user 10 performing aspecified activity is determined, thereby forming an actual set.

This embodiment is advantageous since it facilitates machine learning,as will be described in detail in the following.

Assuming for instance the scenario of Table 2a in the below:

TABLE 2a Database comprising activities and associated objects. ActivityExpected set of objects Activity1 — Activity2 Object1, Object4 Activity3Object5

In this exemplifying embodiment, the tracker device 16 again has accessto one or more specified activities of the user 10, for instance fetchedfrom a calendar app executing on the user's smartphone (exemplified hereas being the tracker device 16), or learned by means of machine learningas previously discussed.

However, in this embodiment, no expected set of objects has yet beenrecorded and associated with newly learned Activity1 (“Go To Work”),which may be learned by the tracker device 16 detecting that it leavesthe home premises between 7 and 8 AM on a weekday at a number ofoccasions.

Again, the tracker device 16 detects in step S101 its location using,e.g., GPS. If the tracker device 16 is leaving the user's 10 homepremises 11 on any weekday at 07:00-08:00, the user is considered topartake in new Activity1, which is learned by the tracker device 16 andadded to Table 2a.

Thereafter, in step S102, the tracker device 16 acquires informationidentifying an expected set of objects which are associated with thedetected activity from the stored database. To this end, the trackerdevice 16 maps the detected activity (“Activity1”) to the entries inTable 2a and concludes that expected set associated with Activity1 notyet comprises any objects.

Further, the tracker device 16 determines in step S103 b the actual setof objects being in proximity of the tracker device 16. As isillustrated in FIG. 8, the tracker device 16 concludes that the wallet12, the home key 13, and the work pass 14, are in proximity to thetracker device 16.

Now, in step S103 c, the tracker device 16 advantageously associates theactual set of objects 12, 13, 14 with the detected activity as a newexpected set of objects, and thus updates Table 2a, resulting in Table2b:

TABLE 2b Updated database comprising activities and associated objects.Activity Expected set of objects Activity1 Object1, Object2, Object3Activity2 Object1, Object4 Activity3 Object5

Advantageously, with this embodiment, machine learning can be applied torecord activities and objects in the database as illustrated in Tables2a and b, and to create appropriate associations between expected setsand corresponding activities.

In an embodiment, machine learning such as association rule miningand/or frequent itemsets (discussed, e.g., in Chapter 6 of “Mining ofMassive Datasets” by J. Leskovec, A. Rajaraman, and J. D. Ullman), isused to deduce an expected set of devices to be associated with aparticular activity.

For instance, a trackder device 16 such as a mobile phone or smartphoneof a user, possibly in combination with further sensing devices, is usedfor building a database of activities and corresponding expected sets ofdevices to be associated with the activities.

In the present example, the tracker device 16 registers that when theuser leaves at home during a weekday at 07:00-08:00, she usually bringsher wallet 12, home key 13, and work pass 14. Upon having registeredthat

-   -   (1) The user leaves at home during a weekday at 07:00-08:00, and        that    -   (2) The user usually brings her wallet, home key and work pass        at these occasions,

at repeated occasions—such as at five different occasion—the trackerdevice 16 (or some other node such as the server 17 and/or a cloudservice), may conclude that

-   -   (1) The user leaving home during a weekday at 07:00-08:00 is a        commonly or routinely performed activity, which is registered as        an activity “Go To Work” (possibly giving the user a chance the        name/define the activity), and that    -   (2) The user usually brings her wallet, home key, and work pass,        upon performing this activity. Thus, the wallet, home key, and        work pass, are registered as an expected set of devices to be        associated with the activity “Go To Work”.

When deducing the expected set, the tracker device 16 may for instancestipulate that any object to be included in the expected set mustfulfill a certain probability threshold, such as having been carried bythe user at 80% of the occasions when the user performed the activity.

Hence, a behaviour (“leave home on a weekday at 07:00-08:00”) of theuser is registered, and if it is concluded that the registered behaviouris a frequently occurring behaviour of the user (e.g., having occurredmore than 5 times), the registered behaviour is registered as anactivity (“Go To Work”).

Further, a group of objects (“wallet, home key, work pass”) isregistered as being carried by the user when the frequently occurringbehaviour (“leave home on a weekday at 07:00-08:00”) of the user isregistered, the group of objects being specified as the expected set ofobjects associated with the specified activity (“Go To Work”).

It is understood that a great number of different activities and acorrespondingly great number of expected sets to be associated with thedifferent activities may be identified by the tracker device 16 andregistered in the database.

FIG. 9 illustrates a sequence diagram where the method of monitoring isperformed in its entirety by the tracker device 16 according to stillanother embodiment.

However, it is noted that this embodiment may also be implemented at aremotely located network node, such as the server 17.

As in the embodiments of FIGS. 5-8, all objects being in proximity tothe tracker device 16 are detected upon detection of the user 10performing a specified activity, thereby forming an actual set.

However, in addition to the steps of the embodiment of FIG. 6, afterhaving determined the actual set of objects 12, 13, 14 in step S103 b,the tracker device 16 queries the user 10 in step S103 d whether theobjects 12, 13, 14 of the determined actual of objects are to be storedas a new expected set for the detected activity.

The user 10 responds to the query in step S103 e, for instance byindicating on a screen of the tracker device 16 (being, e.g., asmartphone) whether all determined objects of the actual set are to beassociated with the detected activity as the new expected set, orwhether a subset of the objects of the actual set is to be associatedwith the detected activity as the new expected set, in response to whichthe tracker device 16 advantageously associates the objects 12, 13, 14indicated by the user 10 with the detected activity as the new expectedset of objects, and thus updates Table 2a, resulting in Table 2b.

The invention has mainly been described above with reference to a fewembodiments. However, a number of scenarios may be envisaged, where acommon feature is that a user is automatically notified of the device(s)she needs at different activities in different times and situations.

1. A doctor is called upon to deal with an activity in the form of anemergency situation where a patient experiences high blood sugar(hyperglycaemia). The expected set associated with this activity maythus comprise (a) a dose of insulin and (b) an injection device (e.g.,being RFID-tagged). If the doctor has forgotten to pack the insulin andinjection upon leaving his clinic, his mobile phone detects the absenceand raises an alarm, so that the doctor realizes this before he leaveshis clinic.

2. When going to court, a lawyer is expected to bring an important casefile. The case file may be RFID-tagged to ensure that his smartwatchwill sound an alarm if he leaves his office for the court proceedingswithout the case file.

3. A mother wants to go out with her family for a picnic. She wants toensure that she carries the high resolution handy-cam to capture thebeautiful moments during their time out. In case of bad weather, shewill also want to bring a garden umbrella. The activity may thus specifya date and time of the picnic, and further weather conditions acquiredfor instance from a weather forecast. Hence, if she leaves home at thespecified date and time, and the forecast predicts bad weather, hersmartphone will notify her if she does not bring the handy-cam and/orthe umbrella.

4. It is detected that the user arrives at home, and the actual set ofobjects is detected. Typically, this is the same set of objects as theset of objects which the user carried when leaving home. If an object ismissing, the user may be notified that she has forgotten an object, orthat an object has been stolen.

Even further, the activity which is performed by the user of thewireless communications device may be detected based on at least one, acombination, or a pattern, of: a location of the wireless communicationsdevice or a change thereof, a motion pattern of the wirelesscommunications device or a change thereof, a date, a time of day, acalendar event, a communication event, or even current weatherconditions. To this end, the behaviour and movements of the user, forinstance the user leaving her home or her office, or whether the user isout running and suddenly stops (or starts) running, time windows, suchas a particular time of the day, or a particular weekday derived forinstance from a meeting event or itinerary information in a digitalcalendar, or even sensor information, where for instance the user'ssmartwatch alerts the user in case skin temperature measured by anIoT-type temperatures arranged in a garment of the user exceeds athreshold value, the activity being defined e.g. as “User CatchingFever”.

With reference to FIG. 10, the steps of the method performed by thetracker device 16, or the server 17, or a distributed cloud solution,according to embodiments are in practice performed by a processing unit20 embodied in the form of one or more microprocessors arranged toexecute a computer program 21 downloaded to a suitable storage medium 22associated with the microprocessor, such as a Random

Access Memory (RAM), a Flash memory or a hard disk drive. The processingunit 20 is arranged to cause the device 16 to carry out the methodaccording to embodiments when the appropriate computer program 31comprising computer-executable instructions is downloaded to the storagemedium 32 and executed by the processing unit 30. The storage medium 32may also be a computer program product comprising the computer program31. Alternatively, the computer program 31 may be transferred to thestorage medium 32 by means of a suitable computer program product, suchas a Digital Versatile Disc (DVD) or a memory stick. As a furtheralternative, the computer program 31 may be downloaded to the storagemedium 32 over a network. The processing unit 30 may alternatively beembodied in the form of a digital signal processor (DSP), an applicationspecific integrated circuit (ASIC), a field-programmable gate array(FPGA), a complex programmable logic device (CPLD), etc.

FIG. 11 illustrates a device 16 configured to monitor objects capable ofwireless communication. The device 16 comprises detecting means 30adapted to detect an activity performed by a user of a wirelesscommunications device, acquiring means 31 adapted to acquire informationidentifying an expected set of objects which are associated with thedetected activity, and determining means 32 adapted to determine whetherat least one of the objects in the expected set is not in proximity ofthe wireless communications device. Further, the device 16 comprisesnotifying means 33 adapted to notify the user that at least one of theobjects in the expected set is not in proximity of the wirelesscommunications device

The device 16 may further comprise a communications interface forreceiving and providing information, and further a local storage forstoring data, and may (in analogy with that previously discussed) beimplemented by a processor embodied in the form of one or moremicroprocessors arranged to execute a computer program downloaded to asuitable storage medium associated with the microprocessor, such as aRAM, a Flash memory or a hard disk drive.

As is readily appreciated by a person skilled in the art, otherembodiments than the ones disclosed above are equally possible withinthe scope of the invention, as defined by the appended patent claims.

1. A method of monitoring objects capable of wireless communications,the method comprising: detecting an activity performed by a user of awireless communications device; acquiring information identifying anexpected set of objects which are associated with the detected activity;determining whether at least one of the objects in the expected set isnot in proximity of the wireless communications device; and if sonotifying the user that at least one of the objects in the expected setis not in proximity of the wireless communications device.
 2. The methodaccording to claim 1, further comprising: determining an actual set ofobjects which are in proximity of the wireless communications device,wherein the determining whether at least one of the objects in theexpected set is not in proximity of the wireless communications devicecomprises: determining whether at least one of the objects in theexpected set is not in the actual set.
 3. The method according to claim2, further comprising: querying the user whether any objects of thedetermined actual set of objects are to be added to the expected set ofobjects for the detected activity; receiving from the user, in responseto the query, an indication from the user regarding which objects of thedetermined actual set are to be included in the expected set; andupdating the expected set of objects associated with the detectedactivity to further include the user-indicated objects of the determinedactual set.
 4. The method according to claim 2, further comprising:storing the determined actual set of objects as a new expected setassociated with the detected activity, if information identifying anexpected set of objects is not available.
 5. The method according toclaim 4, further comprising: querying the user whether the objects ofthe determined actual of objects are to be stored as the new expectedset of objects for the detected activity; and receiving from the user,in response to the query, an indication from the user regarding whichobjects of the determined actual set are to be included in the newexpected set, wherein the step of storing the determined actual set ofobjects as a new expected set associated with the detected activitycomprises: storing the user-indicated objects of the determined actualset as the new expected set associated with the detected activity. 6.The method according to claim 1, further comprising: receiving from theuser, in response to notifying the user that at least one of the objectsin the expected set is not in proximity of the wireless communicationsdevice, an indication that one or more objects in the expected setshould be removed from the expected set for the detected activity; andupdating the expected set of objects associated with the detectedactivity to remove the user-indicated objects from the expected setwhich is associated with the detected activity.
 7. The method accordingto claim 1, wherein the activity which is performed by the user of thewireless communications device is detected based on at least one, acombination, or a pattern, of: a location of the wireless communicationsdevice or a change thereof, a motion pattern of the wirelesscommunications device or a change thereof, a date, a time of day, acalendar event, a communication event, sensor readings, and currentweather conditions.
 8. The method according to claim 1, wherein abehaviour of the user is registered, and if it is concluded that theregistered behaviour is a frequently occurring behaviour of the user,the registered behaviour is specified as an activity.
 9. The methodaccording to claim 8, wherein a group of objects are registered as beingcarried by the user when said frequently occurring behaviour of the useris registered, the group of objects being specified as the expected setof objects associated with the specified activity.
 10. The methodaccording to claim 1, wherein the user is notified by at least one of:emitting an audible sound, displaying a message, generating a hapticnotification, and triggering another wireless communications device tonotify the user.
 11. The method according to claim 1, wherein theinformation identifying the expected set of objects is retrieved from adatabase.
 12. The method according to claim 1, being performed by thewireless communications device.
 13. The method according to claim 1,being performed by a node of a communications network which isaccessible by the wireless communications device, or one or more nodesof a cloud environment which is accessible by the wirelesscommunications device.
 14. The method according to claim 13, furthercomprising: acquiring, from the wireless communications device,information regarding which objects are in proximity of the wirelesscommunications device.
 15. A device for monitoring objects capable ofwireless communications, the device comprising a processing unit and amemory, said memory containing instructions executable by saidprocessing unit, whereby the device is operative to: detect an activityperformed by a user of a wireless communications device; acquireinformation identifying an expected set of objects which are associatedwith the detected activity; determine whether at least one of theobjects in the expected set is not in proximity of the wirelesscommunications device; and if so to notify the user that at least one ofthe objects in the expected set is not in proximity of the wirelesscommunications device.
 16. The device according to claim 15, beingfurther operative to: determine an actual set of objects which are inproximity of the wireless communications device; and further to, whendetermining whether at least one of the objects in the expected set isnot in proximity of the wireless communications device: determinewhether at least one of the objects in the expected set is not in theactual set.
 17. The device according to claim 16, being furtheroperative to: query the user whether any objects of the determinedactual set of objects are to be added to the expected set of objects forthe detected activity; receive from the user, in response to the query,an indication from the user regarding which objects of the determinedactual set are to be included in the expected set; and update theexpected set of objects associated with the detected activity to furtherinclude the user-indicated objects of the determined actual set.
 18. Thedevice according to claim 16, being further operative to: store thedetermined actual set of objects as a new expected set associated withthe detected activity, if information identifying an expected set ofobjects is not available.
 19. The device according to claim 18, beingfurther operative to: query the user whether the objects of thedetermined actual set of objects are to be stored as the new expectedset of objects for the detected activity; and receive from the user, inresponse to the query, an indication from the user regarding whichobjects of the determined actual set are to be included in the newexpected set; and being further operative, when storing the determinedactual set of objects as a new expected set associated with the detectedactivity, to: store the user-indicated objects of the determined actualset as the new expected set associated with the detected activity. 20.The device according to claim 15, being further operative to: receivefrom the user, in response to notifying the user that at least one ofthe objects in the expected set is not in proximity of the wirelesscommunications device, an indication that one or more objects in theexpected set should be removed from the expected set for the detectedactivity; and update the expected set of objects associated with thedetected activity to remove the user-indicated objects from the expectedset which is associated with the detected activity. 21.-30. (canceled)